Optimizing a supply chain problem is a complex task. Generally, supply chain management refers to the flow of products from a production site through intermediate locations to the site of final use. In simple terms, a supply chain management (SCM) problem may be described as follows: products may be produced (or obtained) from a variety of sources for a variety of costs, while at the same time, product must be distrusted to a variety of customers. Note that this is different from a traditional delivery optimization problem. In the delivery optimization scenario, a specific product must be delivered from an origin to a destination, and the essential problem is how to deliver a set of products most efficiently. An SCM problem may be substantially complicated, however, when the product in question is a commodity product, such as industrial liquids. In this case, the commodity product delivered to any given destination may be produced (or obtained) from any available source. Because of this, adding a production side to an SCM problem substantially complicates the optimization process.
Currently, optimization systems are available to optimize the distribution side of an SCM problem. These systems typically identify a set of delivery routes for a set of deliveries from specified locations. Such systems are often constrained, however, by an inability to account for different production possibilities. At the same time, at least for the producer and distributor of commodity materials, energy costs often vary widely from location to location, different plants have different cost and production profiles, and clients' rates of usage of the commodity product may vary. Thus, selecting a production strategy may have a significant impact on operational costs. In fact, for the production and distribution of industrial liquids, the largest cost component of production and distribution may be the cost of power used by production plants. In such a case, a system configured to optimize the distribution of products may produce results that are far from optimal. This occurs as it is often favorable to produce materials at a production plant with very low production costs, even where this may significantly increase transportation costs for some deliveries. Current optimization systems, however, often fail to account for these scenarios.
Accordingly, there remains a need for optimization techniques that are able to optimize both the production side and distribution side of an SCM problem for the producer and distributor of a commodity product.